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Migrating Critical Traffic At Scale with No Downtime?—?Part 2

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 2 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. This is where large-scale system migrations come into play.

Traffic 279
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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

This blog post will share broadly-applicable techniques (beyond GraphQL) we used to perform this migration. By the summer of 2020, many UI engineers were ready to move to GraphQL. To determine customer impact, we could compare various metrics such as error rates, latencies, and time to render.

Traffic 353
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Uber’s Big Data Platform: 100+ Petabytes with Minute Latency

Uber Engineering

To accomplish this, Uber relies heavily on making data-driven decisions at every level, from forecasting rider demand during high traffic events to identifying and addressing bottlenecks … The post Uber’s Big Data Platform: 100+ Petabytes with Minute Latency appeared first on Uber Engineering Blog.

Big Data 109
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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

This introductory blog focuses on an overview of our journey. Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. This architecture shift greatly reduced the processing latency and increased system resiliency. divide the input video into small chunks 2.

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Growth Engineering at Netflix?—?Automated Imagery Generation

The Netflix TechBlog

Growth Engineering at Netflix?—?Automated In the Growth Engineering team, we refer to this as the top of the signup funnel. For more background on the signup funnel and Growth Engineering’s role in the signup funnel, please read our initial post on the topic: Growth Engineering at Netflix? Accelerating Innovation.

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Automated Change Impact Analysis with Site Reliability Guardian

Dynatrace

This is where Site Reliability Engineering (SRE) practices are applied. SREs use Service-Level Indicators (SLI) to see the complete picture of service availability, latency, performance, and capacity across various systems, especially revenue-critical systems.

DevOps 224
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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

This blog post presents how our current iteration of Titus deals with high API call volumes by scaling out horizontally. In that scenario, the system would need to deal with the data propagation latency directly, for example, by use of timeouts or client-originated update tracking mechanisms. How do I know that my cache is up to date?

Cache 224